Azure Data Architect with DevOps || Contract Role

Overview

Remote
Depends on Experience
Contract - Independent
Contract - W2
Contract - 12 Month(s)

Skills

Data Architecture
Governance
Cloud
Azure
SQL
Python
Data Lake
ETL
DevOps
Scripting

Job Details

Data Architect (Azure/DevOps) || Contract Role || Initially hybrid at PA

Required Role Expectation:

Extensive experience (10+ years) in data engineering, data governance, or cloud data architecture.

  • Ability to architect end-to-end solutions should be able to share screen and whiteboard during the interview
  • Work closely with data scientists, engineers, business stakeholders, and cloud teams to translate business requirements into technical solutions.
  • Lead teams, provide mentorship, and guide architectural best practices like Medallion architecture data design pattern and modern lake house implementation.
  • Monitor cloud data solutions for performance, scalability, and cost, implementing optimizations to reduce cloud spend and improve efficiency.

Required Tech Skills

  • Strong skills in SQL, Python, Spark, and Azure cloud environment.
  • Designed and maintained conceptual, logical, and physical data models using Erwin.
  • Hands-on expertise with Databricks platform, Unity Catalog, Delta Lake, and Lakehouse architecture and streaming platforms like Kafka.
  • Azure Cloud Proficiency:
    • Strong knowledge of Azure services, particularly:
      • Azure Virtual Machines, Azure Storage, Azure Networking.
      • Azure Data Factory, Azure Data Lake, Azure Synapse.
      • Azure Logic Apps, Azure Function App, Event Grid (for integration).
    • Experience with Azure Resource Manager (ARM) templates or Terraform for infrastructure provisioning.
  • Data Integration and Migration:
    • Proficiency in data integration techniques and tools.
    • Experience with ETL (Extract, Transform, Load) processes.
  • DevOps and CI/CD:
    • Understanding of DevOps principles and practices.
    • Experience with CI/CD pipelines using tools like Azure DevOps, Jenkins, or similar.
  • Scripting and Automation:
    • Build Testing and Validation Strategy
    • Familiarity in scripting languages like PowerShell or Python.

Good to Have:

  • Designing and Implementing Conversational Interfaces(Conversational BI), Data Preparation and Management, Natural Language Processing (NLP) and Query Handling
  • Proficiency in programming languages such as Java, or JavaScript, Python
  • Knowledge in BI tools (e.g., Power BI, Tableau, ThoughtSPot, LookerStudio), and data querying languages like SQL
  • Strong understanding of NLP, machine learning, AI frameworks, Generative AI and large language models (LLMs).
  • Understanding of Azure Databricks Genie, Hive Meta

Thanks,

IT First Source

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